Are you familiar with the A* algorithm? A heuristic function is typically used in (state-)space search problems: at a given point, you may have alternative "paths" you can choose and the heuristic will help you estimate/predict how "successful" exploring that branch would be by giving a score. The function usually involves reviewing your path so far and trying to look ahead before making another step. More generally, heuristic decision making is a process where you choose an action (the "path") according to your current knowledge (your state) and some prediction criteria which is not necessarily the best, but the most promising. A heuristic search rule could look like this: rule "Example" when // you have a current state, given by one or more patterns $here : CurrentState( $history : path ) // then you query for / generate a list of possible follow-up alternatives ?possiblePath( $here, $nextFromHere ) // optionally, you filter those which make sense qualitatively Filter( ... ) from $nextFromHere // notice: $nextFromHere might not be in the WM // optionally, and/or you apply some heuristic scoring function, filtering quantitatively // notice that it might use the history, the current position or the next tentative step $score : Double( this> THRESHOLD ) from heur( $path, $here, $nextFromHere ) // any additional logic, e.g. accumulate scores? .... then // make your choice insert ( new Step( $nextFromHere ) ); // the step will later modify the currentState end Notice that the following MUCH simplified version - a rule - is doing the same thing... Simply, there is only one promising and meaningful path - e.g. administering an aspiring - which is automatically chosen given the current state (of Fever). rule "a more traditional rule" when $path : MedicalHistory( ... ) $here : FeverDiagnosis( temp< 38 ) // ?possiblePath( $here, $nextFromHere ) --> let's say aspirin, strong antibiotics and bone marrow transplant // but you can already figure out the scores a realistic function would give to the alternatives... // (ok, allergies from $path would make it different, but ignore...) // $score : Double( this> THRESHOLD ) from heur( $path, $here, $nextFromHere ) then // so you hardcode your choice! insert( new AspirinAdministration() ); end Drools Planner is slightly different: you might indeed use it to define a plan - i.e. a sequence of actions to reach a goal - ***provided*** that you can reliably estimate the consequences of any action (move) you allow. Planner, however, already implements its own search strategies. What you provide there is a "score" for the current state (aka candidate "solution"), expressed in terms of hard and soft constraints, that planner algorithms will consume. You still have to provide the alternative moves and their effects, but the main difference between the scoring (the constraints) and heuristic function is that the former usually just look at the current state. So, in planner 1) you tentatively make a step and evaluate the results, 2) then backtrack and repeat until you have seen all possible paths, 3) you choose the best one according to the strategy (it's called meta-heuristic) With a heuristic function, you evaluate your possible future outcome (not just one step ahead) before you do make the step, so that's "predictive". Now, coming back to your question : how do you implement a heuristic function? The answer is: first you have to define it, given your problem :) Only then you can think of an implementation, but functions(), queries and rules with optional accumulates seem good candidates! Best Davide -- View this message in context: http://drools.46999.n3.nabble.com/How-to-write-a-Heuristic-Knowledge-in-D... Sent from the Drools: User forum mailing list archive at Nabble.com. _______________________________________________ rules-users mailing list rules-users(a)lists.jboss.org https://lists.jboss.org/mailman/listinfo/rules-users